A Stochastic Model Incorporating the Effect of Weather Conditions on Anthracnose Development in Stylosanthes scabra

Spatial and temporal progress of anthracnose caused by Colletotrichum gloeosporioides in quantitatively resistant accessions of the tropical pasture legume Stylosanthes scabra were studied in a field experiment at the Southedge Research Station, Queensland, Australia. In a previously published work a conditional ordinal logistic regression model was developed to explain the probability of a plant developing a given disease severity level, depending on its previous disease state and that of its neighbours. In the present study this model is augmented to incorporate the effects of three weather variables which were measured daily during a growing season. Two approaches were used: (a) threshold values for relative humidity (RH), rainfall and net evaporation were used to classify days as suitable or unsuitable for anthracnose growth; (b) days were assumed to vary continuously in their rate of anthracnose growth depending on the numerical values of the weather variables. High 9am RH, low net evaporation and low 9am temperatures are significantly associated with anthracnose growth. Net evaporation proved to be a better index than rainfall and heavy rainfall was not conducive to high levels of anthracnose; however, rainfall was useful once evaporation was taken into account. The effect of 9am RH can be described either by a threshold value around 70% or by a quadratic function. A two-variable model with net evaporation and log(rain+1) explains 97.6% of the available deviance.     

Korean Risk Assessment Model for Breast Cancer Risk Prediction

Purpose

We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk.

Methods

Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail''s equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort.

Results

The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (p<0.001 and <0.001, respectively). The observed incidence of breast cancer in the two cohorts was similar to the expected incidence from the KoBCRAT (KMCC, p = 0.880; NCC, p = 0.878). The AUC using the KoBCRAT was 0.61 for the KMCC and 0.89 for the NCC cohort.

Conclusions

Our findings suggest that the KoBCRAT is a better tool for predicting the risk of breast cancer in Korean women, especially urban women.     

Algal Population Growth Model Integrated with Toxicokinetics for Ecological Risk Assessment under Time-Varying Pesticide Exposure

An algal population growth model integrated with toxicokinetics was developed for assessing the effect of pesticides on population dynamics. This model is a simple one-compartment, first-order kinetic model in which toxicity (growth inhibition and mortality) depends on the intracellular effective concentration of a pesticide at a target site. The model's parameters were derived using an experimental study that investigated the effects of pretilachlor, bensulfuron-methyl, pentoxazone, and quinoclamine on the growth, mortality, and subsequent population recovery of the green alga Pseudokirchneriella subcapitata. Modeled and measured trajectories of algal population dynamics agreed well. The effect on population recovery was underestimated by the model that ignored the toxicokinetics. The four tested herbicides had a variety of toxicity characteristics and physicochemical properties, indicating the wide range of the model's applicability. Moreover, the developed model and the obtained model's parameters were extrapolated to predict long-term algal population dynamics under time-varying herbicide exposure. The calculated integral biomass lost compared with the control was considered a quantitative index of the population-level ecological risk. The model's prediction showed that the same exposure level (peak concentration is equivalent to EC50) indicated much different population-level effect depending on the herbicide.     

A Risk Assessment Model for Type 2 Diabetes in Chinese

Aims

To develop a risk assessment model for persons at risk from type 2 diabetes in Chinese.

Materials and Methods

The model was generated from the cross-sectional data of 16246 persons aged from 20 years old and over. C4.5 algorithm and multivariate logistic regression were used for variable selection. Relative risk value combined with expert decision constructed a comprehensive risk assessment for evaluating the individual risk category. The validity of the model was tested by cross validation and a survey performed six years later with some participants.

Results

Nine variables were selected as risk variables. A mathematical model was established to calculate the average probability of diabetes in each cluster''s group divided by sex and age. A series of criteria combined with relative RR value (2.2) and level of risk variables stratified individuals into four risk groups (non, low, medium and high risk). The overall accuracy reached 90.99% evaluated by cross-validation inside the model population. The incidence of diabetes for each risk group increased from 1.5 (non-risk group) to 28.2(high-risk group) per one thousand persons per year with six years follow-up.

Discussion

The model could determine the individual risk for type 2 diabetes by four risk degrees. This model could be used as a technique tool not only to support screening persons at different risk, but also to evaluate the result of the intervention.     

Development of Relative Risk Model for Regional Groundwater Risk Assessment: A Case Study in the Lower Liaohe River Plain,China

Increasing pressure on water supply worldwide, especially in arid areas, has resulted in groundwater overexploitation and contamination, and subsequent deterioration of the groundwater quality and threats to public health. Environmental risk assessment of regional groundwater is an important tool for groundwater protection. This study presents a new approach for assessing the environmental risk assessment of regional groundwater. It was carried out with a relative risk model (RRM) coupled with a series of indices, such as a groundwater vulnerability index, which includes receptor analysis, risk source analysis, risk exposure and hazard analysis, risk characterization, and management of groundwater. The risk map is a product of the probability of environmental contamination and impact. The reliability of the RRM was verified using Monte Carlo analysis. This approach was applied to the lower Liaohe River Plain (LLRP), northeastern China, which covers 23604 km². A spatial analysis tool within GIS which was used to interpolate and manipulate the data to develop environmental risk maps of regional groundwater, divided the level of risk from high to low into five ranks (V, IV, III, II, I). The results indicate that areas of relative risk rank (RRR) V cover 2324 km², covering 9.8% of the area; RRR IV covers 3986 km², accounting for 16.9% of the area. It is a new and appropriate method for regional groundwater resource management and land use planning, and is a rapid and effective tool for improving strategic decision making to protect groundwater and reduce environmental risk.     

Machinery Risk Assessment for Risk Reduction

New avenues are reviewed and discussed for preventing industrial machine-related injury by means of realistic risk evaluation and reduction processes at the design and application stages of machinery development and use. U.S. guidelines and European standards on machinery risk assessment procedures are described. Applications of risk assessment for machine-related injury risk management and teaching machine-risk control are discussed.     

Ten Years of the Relative Risk Model and Regional Scale Ecological Risk Assessment

It has been 10 years since the publication of the relative risk model (RRM) for regional scale ecological risk assessment. The approach has since been used successfully for a variety of freshwater, marine, and terrestrial environments in North America, South America, and Australia. During this period the types of stressors have been expanded to include more than contaminants. Invasive species, habitat loss, stream alteration and blockage, temperature, change in land use, and climate have been incorporated into the assessments. Major developments in the RRM have included the extensive use of geographical information systems, uncertainty analysis using Monte Carlo techniques, and its application to retrospective assessments to determine causation. The future uses of the RRM include assessments for forestry and conservation management, an increasing use in invasive species evaluation, and in sustainability. Developments in risk communication, the use of Bayesian approaches, and in uncertainty analyses are on the horizon.     

Development of a Microbial Model for the Combined Effect of Temperature and pH on Spoilage of Ground Meat, and Validation of the Model under Dynamic Temperature Conditions

The changes in microbial flora and sensory characteristics of fresh ground meat (beef and pork) with pH values ranging from 5.34 to 6.13 were monitored at different isothermal storage temperatures (0 to 20°C) under aerobic conditions. At all conditions tested, pseudomonads were the predominant bacteria, followed by Brochothrix thermosphacta, while the other members of the microbial association (e.g., lactic acid bacteria and Enterobacteriaceae) remained at lower levels. The results from microbiological and sensory analysis showed that changes in pseudomonad populations followed closely sensory changes during storage and could be used as a good index for spoilage of aerobically stored ground meat. The kinetic parameters (maximum specific growth rate [μ_max] and the duration of lag phase [λ]) of the spoilage bacteria were modeled by using a modified Arrhenius equation for the combined effect of temperature and pH. Meat pH affected growth of all spoilage bacteria except that of lactic acid bacteria. The “adaptation work,” characterized by the product of μ_max and λ(μ_max × λ) was found to be unaffected by temperature for all tested bacteria but was affected by pH for pseudomonads and B. thermosphacta. For the latter bacteria, a negative linear correlation between ln(μ_max × λ) and meat pH was observed. The developed models were further validated under dynamic temperature conditions using different fluctuating temperatures. Graphical comparison between predicted and observed growth and the examination of the relative errors of predictions showed that the model predicted satisfactorily growth under dynamic conditions. Predicted shelf life based on pseudomonads growth was slightly shorter than shelf life observed by sensory analysis with a mean difference of 13.1%. The present study provides a “ready-to-use,” well-validated model for predicting spoilage of aerobically stored ground meat. The use of the model by the meat industry can lead to effective management systems for the optimization of meat quality.     

Approaches for Integrated Risk Assessment

Recognizing the need to enhance the effectiveness and efficiency of risk assessments globally, the World Health Organization's International Programme on Chemical Safety, the U.S. Environmental Protection Agency, the European Commission, and the Organization for Economic Cooperation and Development developed a collaborative partnership to foster integration of assessment approaches used to evaluate human health and ecological risks. The objectives of this effort included: improving understanding of the benefits of integration, identifying obstacles to the integration process, and engaging key agencies, organizations, and scientific societies to promote integration. A framework with supporting documentation was developed to describe an approach for integration. Four case studies were constructed to illustrate how integrated risk assessments might be conducted for chemical and nonchemical stressors. The concepts and approaches developed in the project were evaluated in an international workshop. The goal of this effort was international acceptance of guidance for integrated risk assessment.     

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.     

A Model for Estimation of Water Flow Resistance in Soil-Leaf Pathway under Dynamic Conditions

The present study was carried out to establish a model for estimatingwater flow resistance in a soil-leaf pathway under field conditions.In this model, the change in leaf water content is taken intoconsideration; the model is based on the assumption that waterflow resistance is essentially constant for relatively shortperiods. Resistance was estimated for three subtropical woodyspecies growing on shallow-soiled ridges. For the estimation,transpiration rate and leaf water potential were measured directlyin the field, and leaf water content was estimated based onthe relationship between leaf water potential and relative leafwater content as observed in the laboratory. Resistance showedlittle variation with change in leaf water potential and transpirationrate by day but was particularly high in the evening in allspecies. The reason for this is not known but was perhaps dueto inaccurate measurement for transpiration rate. It was consideredto be pertinent to compare daily values of resistance so asto assess plant adaptation to drought. The model was shown tobe useful for estimating resistance from conventional measurementsin the field. Key words: Leaf water content, leaf water potential, transpiration rate, water flow resistance     

Physiological Factors Responsible for the Development of Osteopenia under Conditions of Mechanical Unloading

A summary of results of investigations by the author and a brief review of some literature data on human bone tissue deprived of mechanical loading (spaceflight, hypokinesia) is given. The direction and markedness of changes in bone mass—the bone mineral density and the bone mineral content—in different skeletal segments depend on their position relative to the gravity vector. A theoretically expected bone mass reduction was revealed in the trabecular structures of the bones of the lower part of the skeleton (local osteopenia). In the upper part of the skeleton, an increase in the bone mineral content is observed, which is considered as a secondary response and is due to redistribution of body fluids cephalad. The main cause of osteopenia is mechanical unloading. Arguments are presented that osteocyte osteolysis, delayed osteoblast histogenesis, and osteoclast resorption provoked by rearrangement in the hierarchy of the systems of volume regulation, ion regulation, and the endocrine regulation of calcium homeostasis are the main mechanisms of osteopenia.     

Framework for Human Health Risk Assessment

The U.S. Environmental Protection Agency has recognized the need to develop a framework for human health risk assessment that puts a perspective on the approaches in practice throughout the Agency. In response, the Agency's Risk Assessment Forum has begun the long-term process of developing a framework for human health risk assessment. The framework will be a communication piece that will lay out the scientific basis, principles, and policy choices underlying past and current risk assessment approaches and will provide recommendations for integrating/harmonizing risk assessment methodologies for all human health endpoints.     

On Aggregating Species for Risk Assessment

Different combinations of species characteristics like dietary strategies and foraging tactics define unique pathways for material cycling and energy flow in ecosystems. I used multivariate cluster analysis on a species attribute matrix to identify groups of species with similar vulnerabilities of exposure to contaminants. The clusters of species may also have similar functions in ecosystems, because they use similar resources in similar ways. Cluster analyses produced hierarchical dendrograms of species relationships that were difficult to characterize with simple labels like herbivore or insectivore. Regardless of whether multivariate analyses are used for aggregating species into exposure guilds, the species attribute matrix is a concise statement of assumptions about how species function in ecosystems. By using species characteristics to aggregate and define assessments, it is hoped that assessment endpoints will be ecologically relevant.     

The Effect of Weather Conditions on Eutrophication in the Neva River Estuary

Analysis of long-term data on chlorophyll a and total phosphorus concentrations, plankton primary production, organic matter mineralization, and weather conditions in the middle of summer in 2003–2017 revealed eutrophication processes in the Neva River estuary. Weather conditions in the region exerted a strong effect on organic matter prodaction and mineralization processes in the estuary. Rainy and cold summers of the recent years promoted massive development of algae due to increased washout of nutrients from the catchment area, but the rate of organic matter mineralization in the water column was reduced because of low water temperature.     

Framework for Human Health Risk Assessment

The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the USEPA. The U.S. Government has the right to retain a nonexclusive royalty-free license in and to any copyright covering this article. The U.S. Environmental Protection Agency has recognized the need to develop a framework for human health risk assessment that puts a perspective on the approaches in practice throughout the Agency. In response, the USEPA's Risk Assessment Forum has begun the process of developing a framework for human health risk assessment. This paper provides some additional background to the previous review of the framework efforts and notes the Agency's extramural efforts to begin the process of integrating and harmonizing risk assessment approaches for all human health endpoints.     

An Assessment of Integrated Risk Assessment

In order to promote international understanding and acceptance of the integrated risk assessment process, the World Health Organization/International Programme on Chemical Safety (WHO/IPCS), in collaboration with the U.S. Environmental Protection Agency and the Organization for Economic Cooperation and Development, initiated a number of activities related to integrated risk assessment. In this project, the WHO/IPCS defines integrated risk assessment as a science-based approach that combines the processes of risk estimation for humans, biota, and natural resources in one assessment. This article explores the strengths and weaknesses of integration as identified up to this date and the degree of acceptance of this concept by the global risk assessment/risk management community. It discusses both opportunities and impediments for further development and implementation.

The major emerging opportunities for an integrated approach stem from the increasing societal and political pressure to move away from vertebrate testing leading to a demand for scientific integrated approaches to in vitro and in vivo testing, as well as to computer simulations, in so-called Intelligent Testing Strategies. In addition, by weighing the evidence from conventional mammalian toxicology, ecotoxicology, human epidemiology, and eco-epidemiology, risk assessors could better characterize mechanisms of action and the forms of the relationships of exposures to responses. It is concluded that further demonstrations of scientific, economic and regulatory benefits of an integrated approach are needed. As risk assessment is becoming more mechanistic and molecular this may create an integrated approach based on common mechanisms and a common systems-biology approach.     

A Regional Multiple Stressor Risk Assessment of the Codorus Creek Watershed Applying the Relative Risk Model

The relative risk model (RRM) used in Port Valdez, AK, and in Oregon's Willamette/McKenzie Watershed was applied to the Codorus Creek Watershed in south central Pennsylvania. The assessment evaluated the relative risk model for its applicability for ranking ecological risks within the Codorus Creek Watershed. The Codorus Creek Watershed approach included ranking stressors and habitats for regions within the watershed. Geographical Information Systems were vital in compiling and comparing stressor and habitat spatial data from regions in the watershed. The risk of ecological impacts to degrade assessment endpoints were calculated and ranked by quantitatively determining the interactions of the stressors and habitats as defined in the conceptual site model. Uncertainty assessment was conducted and the impact upon the relative ranks and risk conclusions evaluated. To determine regional risks, risk management information was gathered identifying areas to be protected, areas of high stress, and areas where additional information is needed. The results supported the applicability of the RRM and suggested areas and stressors for restoration efforts in the Codorus Creek Watershed. Two critical sets of conclusions were drawn from the assessment. First, in the Codorus Creek Watershed, the most significant stressor is agriculture land use, the most significantly impacted endpoint is water quality, and the most vulnerable habitats are those for macroinvertebrates and warm-water fish. Second, this risk assessment demonstrates the feasibility of using the RRM for assessing risk from multiple stressors on habitats with multiple assessment endpoints in an eastern watershed.